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https://issues.apache.org/jira/browse/SPARK-15767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15332519#comment-15332519
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Apache Spark commented on SPARK-15767:
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User 'vectorijk' has created a pull request for this issue:
https://github.com/apache/spark/pull/13690
> Decision Tree Regression wrapper in SparkR
> ------------------------------------------
>
> Key: SPARK-15767
> URL: https://issues.apache.org/jira/browse/SPARK-15767
> Project: Spark
> Issue Type: New Feature
> Components: ML, SparkR
> Reporter: Kai Jiang
> Assignee: Kai Jiang
>
> Implement a wrapper in SparkR to support decision tree regression. R's naive
> Decision Tree Regression implementation is from package rpart with signature
> rpart(formula, dataframe, method="anova"). I propose we could implement API
> like spark.decisionTreeRegression(dataframe, formula, ...) . After having
> implemented decision tree classification, we could refactor this two into an
> API more like rpart()
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